def test_remove_peak_unknown_value(self):
"""Test removing single peak with unknown peak name.
It should throw ValueError exception."""
t = np.arange(0, 2, 0.001)
peak_in = np.random.random(t.size)
with self.assertRaises(ValueError) as context:
Preprocessor._remove_peak(t, peak_in, ptype="unknown")
self.assertTrue("Incorrect ptype value" in str(context.exception))
with self.assertRaises(ValueError) as context:
Preprocessor._remove_peak(t, peak_in, ptype="other")
self.assertTrue("Incorrect ptype value" in str(context.exception))
def test_remove_peak_lorentz(self):
"""Test removing single peak as a Lorentzian peak"""
t = np.arange(0, 3, 0.001)
param_in = np.array([0.8, 2.5, 0.2])
peak_in = self.peak_lorentz(t, param_in[0], param_in[1], param_in[2])
peak_out, param_out = Preprocessor._remove_peak(t,
peak_in,
ptype="lorentz")
self.assertTrue(np.allclose(param_in, param_out),
"Parameters should be the same")
self.assertTrue(np.allclose(peak_in, peak_out),
"Peaks should be the same")
def test_remove_peak_triangle(self):
"""Test removing single peak as a triangle peak"""
t = np.arange(0, 2, 0.001)
param_in = np.array([0.5, 1.5, 0.3])
peak_in = self.peak_triangle(t, param_in[0], param_in[1], param_in[2])
peak_out, param_out = Preprocessor._remove_peak(t,
peak_in,
ptype="triang")
self.assertTrue(np.allclose(param_in, param_out),
"Parameters should be the same")
self.assertTrue(np.allclose(peak_in, peak_out),
"Peaks should be the same")
def test_remove_peak_norm(self):
"""Test removing single peak as a Gaussian peak"""
#If too small segment then it doesn't converge properly
t = np.arange(0, 2, 0.001)
param_in = np.array([1.2, 0.4, 0.1])
peak_in = self.peak_norm(t, param_in[0], param_in[1], param_in[2])
peak_out, param_out = Preprocessor._remove_peak(t,
peak_in,
ptype='norm')
self.assertTrue(np.allclose(param_in, param_out),
"Parameters should be the same")
self.assertTrue(np.allclose(peak_in, peak_out),
"Peaks should be the same")